• Crowdsourcing campaign identifies driver

    From ScienceDaily@1:317/3 to All on Friday, April 01, 2022 22:30:36
    Crowdsourcing campaign identifies drivers of tropical forest loss

    Date:
    April 1, 2022
    Source:
    International Institute for Applied Systems Analysis
    Summary:
    To combat forest loss in the tropics, a new study uses crowdsourcing
    to identify the drivers of deforestation. The resulting dataset
    can be used to create high-resolution maps and help policymakers
    apply the best protection measures.



    FULL STORY ==========================================================================
    To combat forest loss in the tropics, a new study uses crowdsourcing
    to identify the drivers of deforestation. The resulting dataset can be
    used to create high-resolution maps and help policymakers apply the best protection measures.


    ========================================================================== Every year, 10 million hectares of forest disappear worldwide,
    predominantly driven by human activities such as agriculture expansion, building of roads, or wood extraction. To combat this trend and apply
    effective conservation measures, it is crucial to understand the drivers
    behind forest loss.

    In a new study published in Nature Scientific Data,an international
    team of researchers harnessed the power of the crowd and set up a
    crowdsourcing campaign in December 2020 on the Geo-Wiki platform to
    compile data on the drivers of tropical forest loss between 2008 and
    2019. In the analysis, the researchers asked participants to identify
    the predominant and secondary tree loss driver visible in a randomly
    shown location between 30DEG North and South of the equator and to note
    if roads, trails, or buildings were present.

    The campaign was designed as a competition, with prizes offered to
    those who contributed the most, based on a combination of quality and
    quantity. 58 participants from various countries entered and together they reviewed almost 115,000 locations in the tropics, resulting in a dataset
    that has higher spatial resolution than any other such dataset to date.

    "With the high resolution and dense spatial sample of this dataset we
    can create refined maps and get a better understanding of the drivers
    of forest loss during the past decade," says IIASA researcher Juan
    Carlos Laso Bayas, the lead author of the study. "This is crucial
    to orient policymakers towards protecting remaining pristine forests, especially in the face of climate change and biodiversity loss." As well
    as being the first Geo-Wiki campaign focused on tropical deforestation,
    this campaign was also a step-up from previous efforts on Geo-Wiki, by providing participants with extensive training materials and tutorial
    videos, thereby ensuring high data quality. There was also an opportunity
    to talk "face to face" with IIASA experts via a chat service to solve
    any issues that would come up during the campaign.

    The dataset is open-source and is available to use for researchers, policymakers, and the public. A recent study conducted by IIASA
    researchers has already made use of the data, analyzing deforestation in protected areas to gauge the effectiveness of the conservation measures
    and prompt management change where required.

    "Getting involved with scientists through crowdsourcing campaigns such as
    this one is easy, rewarding, and can be of utmost importance to generate
    real change of policies by providing validated data on global events," concludes IIASA researcher and study author Linda See.


    ========================================================================== Story Source: Materials provided by International_Institute_for_Applied_Systems_Analysis.

    Note: Content may be edited for style and length.


    ========================================================================== Journal Reference:
    1. Juan Carlos Laso Bayas, Linda See, Ivelina Georgieva, Dmitry
    Schepaschenko, Olga Danylo, Martina Du"rauer, Hedwig Bartl, Florian
    Hofhansl, Roman Zadorozhniuk, Maksym Burianchuk, Flavius Sirbu,
    Brigitte Magori, Kateryna Blyshchyk, Volodymyr Blyshchyk, Ahmed Harb
    Rabia, Chandra Kant Pawe, Yuan-Fong Su, Merajuddin Ahmed, Kripal
    Panging, Oleksandr Melnyk, Olesia Vasylyshyn, Roman Vasylyshyn,
    Andrii Bilous, Svitlana Bilous, Krishna Das, Reinhard Prestele,
    Ana Pe'rez-Hoyos, Khangsembou Bungnamei, Andrii Lashchenko, Maryna
    Lakyda, Ivan Lakyda, Oleksandr Serediuk, Galyna Domashovets, Yuriy
    Yurchuk, Miche`le Koper, Steffen Fritz. Drivers of tropical forest
    loss between 2008 and 2019.

    Scientific Data, 2022; 9 (1) DOI: 10.1038/s41597-022-01227-3 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2022/04/220401094827.htm

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